{"updated":"2025-01-21T15:58:17.909114+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00090472","sets":["1164:1384:7092:7093"]},"path":["7093"],"owner":"11","recid":"90472","title":["RFPにおける機械学習による非機能要件の評価"],"pubdate":{"attribute_name":"公開日","attribute_value":"2013-03-04"},"_buckets":{"deposit":"d66429e2-cfb4-4511-a153-439aa6f9c0c7"},"_deposit":{"id":"90472","pid":{"type":"depid","value":"90472","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"RFPにおける機械学習による非機能要件の評価","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"RFPにおける機械学習による非機能要件の評価"},{"subitem_title":"Evaluation of RFPs Based on Machine Learning","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"要求","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2013-03-04","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"奈良先端科学技術大学院大学情報科学研究科"},{"subitem_text_value":"奈良先端科学技術大学院大学情報科学研究科"},{"subitem_text_value":"奈良先端科学技術大学院大学情報科学研究科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Information Science, Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Information Science, Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Information Science, Nara Institute of Science and Technology","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/90472/files/IPSJ-SE13179005.pdf"},"date":[{"dateType":"Available","dateValue":"2015-03-04"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SE13179005.pdf","filesize":[{"value":"558.2 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"12"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"2410272f-8782-4967-9463-afef9c732d03","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2013 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"齊藤, 康廣"},{"creatorName":"門田, 暁人"},{"creatorName":"松本, 健一"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yasuhiro, Saito","creatorNameLang":"en"},{"creatorName":"Akito, Monden","creatorNameLang":"en"},{"creatorName":"Kenichi, Matsumoto","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10112981","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本稿では，自然言語で記述された提案依頼書 （Request For Proposal ；以下 RFP とする ）に記載された非機能要件の記述の明確さを機械学習により評価する方法を提案する．提案方法では，まず，RFP から非機能要件に関するキーワード群を抽出し，個々の非機能要件の特性とマッピングさせる．次に，各キーワードの出現頻度と文脈ベクトルに着目して重み付けを行い，ランダムフォレストによって，非機能要件の記述の明確さをモデル化する．70 件の RFP を題材として，提案方法によって多数の非機能要件の記述の明確さを 3 段階で評価した結果，エキスパートによる評価に対する完全一致率の平均が 69.8 %となった．また，完全不一致率 （評価が 2 段階外れること） は極めて小さかった．このことから，エキスパートがいない状況においても，機械学習によって RFP の品質の自動評価をある程度行えることが分かった．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"This paper proposes a machine learning approach to evaluate the clarity of non-functional requirements (NFRs) described in a Request For Proposal (RFP) written in a natural language. In the proposed method, keywords related to NFRs are extracted from a RFP, and mapped to each NFR category. Then, the clarity of NFRs is modeled by the random forest with weight factors based on appearance frequency and context vectors. As a result of an experimental to evaluate the clarity (low, mid or high) of many NFR categories in 70 RFPs, the proposed method showed 69.8% match to the expert's decision. Also, there were few cases where the model concluded as clarity=high while expert concluded clarity=low, and vice versa. These results suggest that the proposed machine learning approach could be used to automatically evaluate the quality of RFP without experts.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告ソフトウェア工学（SE）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2013-03-04","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"5","bibliographicVolumeNumber":"2013-SE-179"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"created":"2025-01-18T23:40:02.794608+00:00","id":90472,"links":{}}